Camera Calibration Using 2D Reference Points
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Solution Overview
Problem
Current camera calibration methods, such as model-based and self-calibration techniques, face challenges in balancing cost and accuracy, particularly in obtaining precise object positioning in computer vision applications, as they often require complex setups or limited parameter calculations.
Innovation Solution
An image positioning method and system that calibrates cameras using two reference points to calculate coordinate transformation parameters, allowing for the transformation of image coordinates to world coordinates, enabling accurate object positioning without the need for complex calibration objects or extensive parameter calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If three-dimensional calibration pattern is adopted, then calibration accuracy is improved, but manufacturing cost and complexity increase significantly
Solution Approach 1:
The patent uses a two-dimensional calibration pattern that replicates the essential geometric features needed for calibration without requiring three-dimensional structure. By capturing multiple views of the 2D pattern, the system achieves 3D calibration accuracy while maintaining 2D manufacturing simplicity
Solution Approach 2:
The patent transitions from requiring 3D calibration objects to using 2D calibration patterns captured from multiple camera angles. By adding the temporal dimension (multiple frames) to the 2D pattern, the system achieves equivalent calibration accuracy to 3D patterns without the manufacturing complexity
2Ease of manufacture
If two-dimensional calibration pattern is adopted, then manufacturing cost is reduced, but calibration accuracy deteriorates due to insufficient space point information
Solution Approach 1:
The patent pre-arranges multiple camera positions and captures multiple frames of the 2D calibration pattern before processing. This preliminary capture of sufficient geometric information from multiple viewpoints enables accurate calibration while maintaining 2D pattern simplicity
Solution Approach 2:
The patent combines information from multiple 2D calibration pattern captures taken from different camera positions. By merging these multiple 2D observations, the system reconstructs sufficient 3D spatial information to achieve high calibration accuracy while using only simple 2D patterns
3Device complexity
If self-calibration method is used, then device complexity is reduced, but positioning accuracy deteriorates because only intrinsic parameters are calculated
Solution Approach 1:
The patent introduces a simple 2D calibration pattern as an intermediary object between the camera and the calibration process. This intermediary provides known geometric references that enable calculation of both intrinsic and extrinsic parameters, achieving high positioning accuracy without complex self-calibration procedures
Solution Approach 2:
The patent changes the approach from calculating only intrinsic parameters (self-calibration) to calculating both intrinsic and extrinsic parameters by introducing a calibration pattern with known geometry. This parameter expansion enables accurate world coordinate positioning while keeping the overall process simple
4Measurement precision
If model-based calibration with multiple calibration objects is used, then calibration accuracy is improved, but time consumption and productivity decrease
Solution Approach 1:
The patent extracts only the essential calibration information needed from a calibration pattern, using a single 2D pattern with key geometric features rather than multiple complex calibration objects. This extraction of essential information maintains calibration accuracy while significantly reducing calibration time and improving productivity
Data Source
AI summary
An image positioning method having following steps is provided. The steps include: obtaining world coordinates of two reference points and image coordinates of two projection points corresponding to the two reference points; calculating a plurality of coordinate transformation parameters relative to transformation between any image coordinates and any world coordinates corresponding to a camera according only to the world coordinates of the two reference points, the image coordinates of the two projection points, and world coordinates of the camera; obtaining an second image having an object image corresponding to an object through the camera; and positioning world coordinates of the object according to the coordinate transformation parameters.